Identify Where Your Plant Is Losing Fuel Value
And understand how that performance can be sustained and extended.
Deterministic analysis of plant operating data to quantify performance drift from best demonstrated operation — forming the basis for measurable recovery and ongoing performance improvement.
Part of a structured performance framework: identify → stabilise → extend.
- · No plant changes or downtime
- · Uses existing DCS / historian exports
- · Results expressed in ₹ and fuel terms
How Performance Is Identified and Sustained
A structured approach to identifying, stabilising, and extending fuel-value performance within existing thermal assets.
ControlAlign™ identifies and quantifies performance drift using plant operating data.
This establishes the measurable gap between current operation and the unit's best demonstrated performance.
The initial objective is to stabilise operation and reduce variability across real operating conditions.
In some cases, further gains may be achieved by improving how heat is transferred within the furnace environment.
What Happens After Performance Is Identified
Once a measurable performance gap is identified, the objective is to:
- stabilise operation around best demonstrated performance
- reduce variability across load conditions
- quantify the economic impact of deviation
Where appropriate, further performance gains may be achieved through improvement in furnace heat transfer behaviour.
This ensures that performance improvement is both measurable and practically realisable.
In cases where performance extension beyond operational stabilisation is required: Learn about HydroHub™ →
Not Just a Diagnostic
ControlAlign™ is not simply a reporting tool. It forms part of a broader performance framework designed to both identify and support the recovery of fuel-value efficiency within existing thermal generation assets.
Request the Data Requirements Guide
We'll send you the ControlAlign™ Data Requirements & Preparation Guide — outlining the required historian data, fuel inputs, and simple DCS export steps. Once data is shared, we proceed directly with analysis.
The diagnostic establishes the gap. The guidance tells your operators what to do about it.
The analysis is fully data-led and derived from the unit's own DCS historian data. It focuses on identifying the unit's best demonstrated operating envelope, quantifying any variance from that state, and translating observed conditions into operator-level control guidance.
Three stages. Commitment at each gate is yours.
The analysis centres on heat transfer effectiveness — the operating conditions under which energy has historically been delivered more effectively to the working fluid, without any increase in fuel input.
Combustion systems lose performance when operating conditions drift from their demonstrated best. The gap is not visible in standard instrumentation — but it is present in every plant's operating history. ControlAlign™ extracts it using a deterministic, repeatable framework derived entirely from your own data.